23 results
128 Resident training in research fundamentals using an online, asynchronous course
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- Jason T Blackard, Jacqueline M. Knapke, Stephanie Schuckman, Jennifer Veevers, William D. Hardie, Ruchi Yadav, Alexa Kahn, Patrick Lee, Sima Terebelo, Patrick H. Ryan
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- Journal:
- Journal of Clinical and Translational Science / Volume 8 / Issue s1 / April 2024
- Published online by Cambridge University Press:
- 03 April 2024, pp. 37-38
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OBJECTIVES/GOALS: Scholarly activity is a key component of most residency programs. To establish fundamental research skills and fill gaps within training curricula, we developed an online, asynchronous set of modules to introduce trainees to various topics that are germane to the conduct of research and evaluated its effectiveness in resident research education. METHODS/STUDY POPULATION: Research 101 was utilized by residents at the Brookdale Hospital Medical Center in Brooklyn, NY. Resident knowledge, confidence, and satisfaction were assessed using pre- and post-module surveys with 5-point Likert scaled questions, open-ended text responses, and a final quiz. RESULTS/ANTICIPATED RESULTS: Pre-module survey results indicated that residents were most confident with the Aligning expectations, Introduction to research, and Study design and data analysis basics modules and least confident with the Submitting an Institutional Review Board (IRB) protocol at UC and Presenting your summer research modules. Post-module survey responses increased significantly compared to pre-module results for all modules and learning objectives (p<0.0001). “This module met my needs” was endorsed 91.4% of the time. A final quiz of 25 multiple choice questions resulted in a median score of 23. Content analysis of open-ended post-module survey responses identified multiple strengths and opportunities for improvement in course content and instructional methods. DISCUSSION/SIGNIFICANCE: These data demonstratethat residents can benefit from completion of Research 101, as post-module survey scores were significantly higher than pre-module survey scores for all modules and questions, and final quiz scores were high and highlighted opportunities for additional resident learning.
Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach – CORRIGENDUM
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, JeanMichel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, HsiChung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil TekolaAyele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 221 / Issue 2 / August 2022
- Published online by Cambridge University Press:
- 04 May 2022, p. 494
- Print publication:
- August 2022
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 220 / Issue 4 / April 2022
- Published online by Cambridge University Press:
- 28 February 2022, pp. 219-228
- Print publication:
- April 2022
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Background
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
AimsTo use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
MethodThis study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
ResultsThe best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
ConclusionsUsing PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Coronavirus Host Genomics Study: South Africa (COVIGen-SA)
- Andrew K. May, Heather Seymour, Harriet Etheredge, Heather Maher, Marta C. Nunes, Shabir A. Madhi, Simiso M. Sokhela, W. D. Francois Venter, Neil Martinson, Firdaus Nabeemeeah, Cheryl Cohen, Jocelyn Moyes, Sibongile Walaza, Stefano Tempia, Jackie Kleynhans, Anne von Gottberg, Jeremy Nel, Halima Dawood, Ebrahim Variava, Stephen Tollman, Kathleen Kahn, Kobus Herbst, Emily B. Wong, Caroline T. Tiemessen, Alex van Blydenstein, Lyle Murray, Michelle Venter, June Fabian, Michéle Ramsay, Omar Enzo Santangelo
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- Journal:
- Global Health, Epidemiology and Genomics / Volume 2022 / 2022
- Published online by Cambridge University Press:
- 01 January 2024, e2
- Print publication:
- 2022
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Host genetic factors are known to modify the susceptibility, severity, and outcomes of COVID-19 and vary across populations. However, continental Africans are yet to be adequately represented in such studies despite the importance of genetic factors in understanding Africa’s response to the pandemic. We describe the development of a research resource for coronavirus host genomics studies in South Africa known as COVIGen-SA—a multicollaborator strategic partnership designed to provide harmonised demographic, clinical, and genetic information specific to Black South Africans with COVID-19. Over 2,000 participants have been recruited to date. Preliminary results on 1,354 SARS-CoV-2 positive participants from four participating studies showed that 64.7% were female, 333 had severe disease, and 329 were people living with HIV. Through this resource, we aim to provide insights into host genetic factors relevant to African-ancestry populations, using both genome-wide association testing and targeted sequencing of important genomic loci. This project will promote and enhance partnerships, build skills, and develop resources needed to address the COVID-19 burden and associated risk factors in South African communities.
Characterisation of age and polarity at onset in bipolar disorder
- Janos L. Kalman, Loes M. Olde Loohuis, Annabel Vreeker, Andrew McQuillin, Eli A. Stahl, Douglas Ruderfer, Maria Grigoroiu-Serbanescu, Georgia Panagiotaropoulou, Stephan Ripke, Tim B. Bigdeli, Frederike Stein, Tina Meller, Susanne Meinert, Helena Pelin, Fabian Streit, Sergi Papiol, Mark J. Adams, Rolf Adolfsson, Kristina Adorjan, Ingrid Agartz, Sofie R. Aminoff, Heike Anderson-Schmidt, Ole A. Andreassen, Raffaella Ardau, Jean-Michel Aubry, Ceylan Balaban, Nicholas Bass, Bernhard T. Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Wade H Berrettini, Marco P. Boks, Evelyn J. Bromet, Katharina Brosch, Monika Budde, William Byerley, Pablo Cervantes, Catina Chillotti, Sven Cichon, Scott R. Clark, Ashley L. Comes, Aiden Corvin, William Coryell, Nick Craddock, David W. Craig, Paul E. Croarkin, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Udo Dannlowski, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Srdjan Djurovic, Howard J. Edenberg, Mariam Al Eissa, Torbjørn Elvsåshagen, Bruno Etain, Ayman H. Fanous, Frederike Fellendorf, Alessia Fiorentino, Andreas J. Forstner, Mark A. Frye, Janice M. Fullerton, Katrin Gade, Julie Garnham, Elliot Gershon, Michael Gill, Fernando S. Goes, Katherine Gordon-Smith, Paul Grof, Jose Guzman-Parra, Tim Hahn, Roland Hasler, Maria Heilbronner, Urs Heilbronner, Stephane Jamain, Esther Jimenez, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, John R. Kelsoe, James L. Kennedy, Tilo Kircher, George Kirov, Sarah Kittel-Schneider, Farah Klöhn-Saghatolislam, James A. Knowles, Thorsten M. Kranz, Trine Vik Lagerberg, Mikael Landen, William B. Lawson, Marion Leboyer, Qingqin S. Li, Mario Maj, Dolores Malaspina, Mirko Manchia, Fermin Mayoral, Susan L. McElroy, Melvin G. McInnis, Andrew M. McIntosh, Helena Medeiros, Ingrid Melle, Vihra Milanova, Philip B. Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Markus M. Nöthen, Tomas Novak, John I. Nurnberger, Niamh O'Brien, Kevin S. O'Connell, Claire O'Donovan, Michael C. O'Donovan, Nils Opel, Abigail Ortiz, Michael J. Owen, Erik Pålsson, Carlos Pato, Michele T. Pato, Joanna Pawlak, Julia-Katharina Pfarr, Claudia Pisanu, James B. Potash, Mark H Rapaport, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Jonathan Repple, Hélène Richard-Lepouriel, Marcella Rietschel, Kai Ringwald, Gloria Roberts, Guy Rouleau, Sabrina Schaupp, William A Scheftner, Simon Schmitt, Peter R. Schofield, K. Oliver Schubert, Eva C. Schulte, Barbara Schweizer, Fanny Senner, Giovanni Severino, Sally Sharp, Claire Slaney, Olav B. Smeland, Janet L. Sobell, Alessio Squassina, Pavla Stopkova, John Strauss, Alfonso Tortorella, Gustavo Turecki, Joanna Twarowska-Hauser, Marin Veldic, Eduard Vieta, John B. Vincent, Wei Xu, Clement C. Zai, Peter P. Zandi, Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics (ConLiGen), Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Arianna Di Florio, Jordan W. Smoller, Joanna M. Biernacka, Francis J. McMahon, Martin Alda, Bertram Müller-Myhsok, Nikolaos Koutsouleris, Peter Falkai, Nelson B. Freimer, Till F.M. Andlauer, Thomas G. Schulze, Roel A. Ophoff
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- Journal:
- The British Journal of Psychiatry / Volume 219 / Issue 6 / December 2021
- Published online by Cambridge University Press:
- 25 August 2021, pp. 659-669
- Print publication:
- December 2021
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Background
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Minimum clinically important differences for the Functioning Assessment Short Test and a battery of neuropsychological tests in bipolar disorders: results from the FACE-BD cohort
- P. Roux, E. Brunet-Gouet, M. Ehrminger, B. Aouizerate, V. Aubin, J. M. Azorin, F. Bellivier, T. Bougerol, P. Courtet, C. Dubertret, J. P. Kahn, M. Leboyer, E. Olié, the FondaMental Advanced Centers of Expertise in Bipolar Disorders (FACE-BD) Collaborators, B. Etain, C. Passerieux
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- Journal:
- Epidemiology and Psychiatric Sciences / Volume 29 / 2020
- Published online by Cambridge University Press:
- 20 July 2020, e144
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Aims
Establishing the minimum clinically important difference (MCID) in functioning and cognition is essential to the interpretation of the research and clinical work conducted in bipolar disorders (BD). The present study aimed to estimate the MCID for the Functioning Assessment Short Test (FAST) and a battery of neuropsychological tests in BD.
MethodsAnchor-based and distributive methods were used to estimate the MCID for the FAST and cognition using data from a large, multicentre, observational cohort of individuals with BD. The FAST and cognition were linked with the Clinical Global Impressions Scale-Severity (CGI-S) and Global Assessment of Functioning (GAF) using an equipercentile method. The magnitude of the standard error measurement (s.e.m.) provided another estimate of the MCID.
ResultsIn total, 570 participants were followed for 2 years. Cross-sectional CGI-S and GAF scores were linked to a threshold ⩽7 on the FAST for functional remission. The MCID for the FAST equalled 8- or 9-points change from baseline using the CGI-S and GAF. One s.e.m. on the FAST corresponded to 7.6-points change from baseline. Cognitive variables insufficiently correlated with anchor variables (all ρ <0.3). One s.e.m. for cognitive variables corresponded to a range of 0.45 to 0.93-s.d. change from baseline.
ConclusionsThese findings support the value of the estimated MCID for the FAST and cognition and may be a useful tool to evaluate cognitive and functional remediation effects and improve patient functional outcomes in BD. The CGI-S and GAF were inappropriate anchors for cognition. Further studies may use performance-based measures of functioning instead.
1857 – Peer Relationships And Adolescents Mental Health: Finding From The Seyle Project In Italy
- M. Iosue, V. Carli, M. D’Aulerio, F. Basilico, L. Recchia, A. Apter, J. Balazs, J. Bobes, R. Brunner, P. Corcoran, D. Cosman, T. Durkee, C. Haring, J.P. Kahn, H. Keeley, D. Marusic, V. Postuvan, F. Resch, P. Saiz, A. Varnik, P. Varnik, C. Wasserman, C. Hoven, M. Sarchiapone, D. Wasserman
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- Journal:
- European Psychiatry / Volume 28 / Issue S1 / 2013
- Published online by Cambridge University Press:
- 15 April 2020, 28-E1107
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Introduction
Peer relationships play a critical role in the development of adolescents, not only for the acquisition of social skills but also for the sense of personal identity and competence. Thus the quality of peer relationships influences actual and future mental health of the adolescent.
ObjectivesSEYLE (Saving and Empowering Young Lives in Europe) is a randomized controlled trial, funded by the EU, evaluating interventions for mental health promotion and suicide prevention. The study comprised 12,395 high-school students from 11 European countries.
AimsWe investigated the differences on psychological problems between students with poor and good peer relationships.
Methods1,195 adolescents (mean age 15.3 ± 0.6; 68% females) from the Molise region constituted the Italian sample. Adolescents were identified as with poor peer relationships if they never or just sometimes get along with people of their age, feel that peers like having them in the group and feel that peers were kind and helpful. Psychometric measures were used to assess mental health problems such as depression (Beck Depression Inventory II), anxiety (Zung Self-Assessment Anxiety Scale), well-being (WHO-5) and suicidal ideation (Paykel Suicide Scale).
ResultsAdolescents who reported poor peer relationships scored significantly higher (p < .005) on the scales assessing depression, anxiety and suicidal ideation and significantly lower (p < .001) on the WHO-5.
ConclusionsParticularly in adolescence peer relationships may influence psychological well-being and vice versa mental health influences the openness to the others. So promoting mental health and contemporary improve social skills could lead adolescents to a better life.
717 – Clinical Measures Trump Neurocognition in Predicting Long-term Outcome for Adolescents at Ultra-high Risk for Psychosis
- T. Ziermans, S. de Wit, P. Schothorst, M. Sprong, H. van Engeland, R. Kahn, S. Durston
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- Journal:
- European Psychiatry / Volume 28 / Issue S1 / 2013
- Published online by Cambridge University Press:
- 15 April 2020, 28-E226
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Background:
Most studies aiming to predict transition to psychosis for individuals at ultra-high risk (UHR) have focused on either neurocognitive or clinical variables and have made little effort to combine the two. We aimed to investigate the relative value of neurocognitive and clinical variables for predicting transition to psychosis as well as long-term functional outcome.
Methods:Sixty-seven adolescents at UHR and 72 controls completed an extensive clinical and neurocognitive assessment. Forty-three UHR individuals and 47 controls participated in long-term follow-up approximately six years later. UHR adolescents who had converted to psychosis (UHR-P) were compared to individuals who had not (UHR-NP) and controls on clinical and neurocognitive variables. Regression analyses were performed to determine which baseline measures best predicted transition to psychosis and long-term functional outcome for UHR individuals.
Results:Low IQ was the single neurocognitive parameter that discriminated UHR-P individuals from UHR-NP individuals and controls. The severity of attenuated positive symptoms was the only significant predictor of a transition to psychosis and disorganized symptoms were highly predictive of functional outcome.
Conclusions:IQ was lowest for those individuals at ultra high risk for psychosis who later went on to have a psychotic episode. However, IQ was not a good predictor of either transition or functional outcome. Rather, clinical measures proved to be the most important vulnerability markers for long-term outcome.
Sleep quality and emotional reactivity cluster in bipolar disorders and impact on functioning
- B. Etain, O. Godin, C. Boudebesse, V. Aubin, J.M. Azorin, F. Bellivier, T. Bougerol, P. Courtet, S. Gard, J.P. Kahn, C. Passerieux, FACE-BD collaborators, M. Leboyer, C. Henry
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- Journal:
- European Psychiatry / Volume 45 / September 2017
- Published online by Cambridge University Press:
- 23 March 2020, pp. 190-197
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Objective:
Bipolar disorders (BD) are characterized by sleep disturbances and emotional dysregulation both during acute episodes and remission periods. We hypothesized that sleep quality (SQ) and emotional reactivity (ER) defined clusters of patients with no or abnormal SQ and ER and we studied the association with functioning.
Method:We performed a bi-dimensional cluster analysis using SQ and ER measures in a sample of 533 outpatients patients with BD (in remission or with subsyndromal mood symptoms). Clusters were compared for mood symptoms, sleep profile and functioning.
Results:We identified three clusters of patients: C1 (normal ER and SQ, 54%), C2 (hypo-ER and low SQ, 22%) and C3 (hyper-ER and low SQ, 24%). C1 was characterized by minimal mood symptoms, better sleep profile and higher functioning than other clusters. Although highly different for ER, C2 and C3 had similar levels of subsyndromal mood symptoms as assessed using classical mood scales. When exploring sleep domains, C2 showed poor sleep efficiency and a trend for longer sleep latency as compared to C3. Interestingly, alterations in functioning were similar in C2 and C3, with no difference in any of the sub-domains.
Conclusion:Abnormalities in ER and SQ delineated three clusters of patients with BD and significantly impacted on functioning.
Importance of Participant-Centricity and Trust for a Sustainable Medical Information Commons
- Amy L. McGuire, Mary A. Majumder, Angela G. Villanueva, Jessica Bardill, Juli M. Bollinger, Eric Boerwinkle, Tania Bubela, Patricia A. Deverka, Barbara J. Evans, Nanibaa' A. Garrison, David Glazer, Melissa M. Goldstein, Henry T. Greely, Scott D. Kahn, Bartha M. Knoppers, Barbara A. Koenig, J. Mark Lambright, John E. Mattison, Christopher O'Donnell, Arti K. Rai, Laura L. Rodriguez, Tania Simoncelli, Sharon F. Terry, Adrian M. Thorogood, Michael S. Watson, John T. Wilbanks, Robert Cook-Deegan
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- Journal:
- Journal of Law, Medicine & Ethics / Volume 47 / Issue 1 / Spring 2019
- Published online by Cambridge University Press:
- 01 January 2021, pp. 12-20
- Print publication:
- Spring 2019
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Drawing on a landscape analysis of existing data-sharing initiatives, in-depth interviews with expert stakeholders, and public deliberations with community advisory panels across the U.S., we describe features of the evolving medical information commons (MIC). We identify participant-centricity and trustworthiness as the most important features of an MIC and discuss the implications for those seeking to create a sustainable, useful, and widely available collection of linked resources for research and other purposes.
Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains
- R. Blakey, S. Ranlund, E. Zartaloudi, W. Cahn, S. Calafato, M. Colizzi, B. Crespo-Facorro, C. Daniel, Á. Díez-Revuelta, M. Di Forti, GROUP, C. Iyegbe, A. Jablensky, R. Jones, M.-H. Hall, R. Kahn, L. Kalaydjieva, E. Kravariti, K. Lin, C. McDonald, A. M. McIntosh, PEIC, M. Picchioni, J. Powell, A. Presman, D. Rujescu, K. Schulze, M. Shaikh, J. H. Thygesen, T. Toulopoulou, N. Van Haren, J. Van Os, M. Walshe, WTCCC2, R. M. Murray, E. Bramon
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- Journal:
- Psychological Medicine / Volume 48 / Issue 8 / June 2018
- Published online by Cambridge University Press:
- 02 November 2017, pp. 1325-1340
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Background
A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.
MethodsThis multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.
ResultsThe P300 amplitude and latency were not associated (regression coef. −0.06, 95% CI −0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10–0.28, p < 0.001). There was no evidence of associations between lateral ventricular volume and the other measures (all p > 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.
ConclusionsThe P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.
Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium
- E. Walton, D. P. Hibar, T. G. M. van Erp, S. G. Potkin, R. Roiz-Santiañez, B. Crespo-Facorro, P. Suarez-Pinilla, N. E. M. van Haren, S. M. C. de Zwarte, R. S. Kahn, W. Cahn, N. T. Doan, K. N. Jørgensen, T. P. Gurholt, I. Agartz, O. A. Andreassen, L. T. Westlye, I. Melle, A. O. Berg, L. Morch-Johnsen, A. Færden, L. Flyckt, H. Fatouros-Bergman, Karolinska Schizophrenia Project Consortium (KaSP), E. G. Jönsson, R. Hashimoto, H. Yamamori, M. Fukunaga, N. Jahanshad, P. De Rossi, F. Piras, N. Banaj, G. Spalletta, R. E. Gur, R. C. Gur, D. H. Wolf, T. D. Satterthwaite, L. M. Beard, I. E. Sommer, S. Koops, O. Gruber, A. Richter, B. Krämer, S. Kelly, G. Donohoe, C. McDonald, D. M. Cannon, A. Corvin, M. Gill, A. Di Giorgio, A. Bertolino, S. Lawrie, T. Nickson, H. C. Whalley, E. Neilson, V. D. Calhoun, P. M. Thompson, J. A. Turner, S. Ehrlich
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- Journal:
- Psychological Medicine / Volume 48 / Issue 1 / January 2018
- Published online by Cambridge University Press:
- 26 May 2017, pp. 82-94
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Background
Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.
MethodsThis study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).
ResultsMeta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (βstd = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.
ConclusionsUsing an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.
Affective lability mediates the association between childhood trauma and suicide attempts, mixed episodes and co-morbid anxiety disorders in bipolar disorders
- M. Aas, C. Henry, F. Bellivier, M. Lajnef, S. Gard, J.-P. Kahn, T. V. Lagerberg, S. R. Aminoff, T. Bjella, M. Leboyer, O. A. Andreassen, I. Melle, B. Etain
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- Journal:
- Psychological Medicine / Volume 47 / Issue 5 / April 2017
- Published online by Cambridge University Press:
- 29 November 2016, pp. 902-912
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Background
Many studies have shown associations between a history of childhood trauma and more severe or complex clinical features of bipolar disorders (BD), including suicide attempts and earlier illness onset. However, the psychopathological mechanisms underlying these associations are still unknown. Here, we investigated whether affective lability mediates the relationship between childhood trauma and the severe clinical features of BD.
MethodA total of 342 participants with BD were recruited from France and Norway. Diagnosis and clinical characteristics were assessed using the Diagnostic Interview for Genetic Studies (DIGS) or the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Affective lability was measured using the short form of the Affective Lability Scale (ALS-SF). A history of childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Mediation analyses were performed using the SPSS process macro.
ResultsUsing the mediation model and covariation for the lifetime number of major mood episodes, affective lability was found to statistically mediate the relationship between childhood trauma experiences and several clinical variables, including suicide attempts, mixed episodes and anxiety disorders. No significant mediation effects were found for rapid cycling or age at onset.
ConclusionsOur data suggest that affective lability may represent a psychological dimension that mediates the association between childhood traumatic experiences and the risk of a more severe or complex clinical expression of BD.
Contributors
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- By Robert S. Anderson, (Mary) Colleen Bhalla, Michelle Blanda, Christopher Carpenter, Chris Chauhan, Paul L. DeSandre, Maura Dickinson, Jonathan A. Edlow, Dany Elsayegh, Kara Iskyan Geren, Peter J. Gruber, Jin H. Han, Marianne Haughey, Teresita M. Hogan, Ula Hwang, Lindsay Jin, Michael P. Jones, Joseph H. Kahn, Keli M. Kwok, Denise Law, Megan M. Leo, Stephen Y. Liang, Judith A. Linden, Brendan G. Magauran Jr, Joseph P. Martinez, Amal Mattu, Karen M. May, Aileen McCabe, Kerry K. McCabe, Jolion McGreevy, Ron Medzon, Ravi K. Murthy, Aneesh T. Narang, Lauren M. Nentwich, David E. Newman-Toker, Jonathan S. Olshaker, Joseph R. Pare, Thomas Perera, Joanna Piechniczek-Buczek, Jesse M. Pines, Timothy Platts-Mills, Suzanne Michelle Rhodes, Lynne Rosenberg, Mark Rosenberg, Todd C. Rothenhaus, Kristine Samson, Arthur B. Sanders, Jeffrey I. Schneider, Rishi Sikka, Kirk A. Stiffler, Morsal R. Tahouni, Mary E. Tanski, Abel Wakai, Scott T. Wilber, Deborah R. Wong
- Edited by Joseph H. Kahn, Brendan G. Magauran, Jr, Jonathan S. Olshaker
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- Book:
- Geriatric Emergency Medicine
- Published online:
- 05 January 2014
- Print publication:
- 16 January 2014, pp vii-x
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Additive effects of childhood abuse and cannabis abuse on clinical expressions of bipolar disorders
- M. Aas, B. Etain, F. Bellivier, C. Henry, T. Lagerberg, A. Ringen, I. Agartz, S. Gard, J.-P. Kahn, M. Leboyer, O. A. Andreassen, I. Melle
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- Journal:
- Psychological Medicine / Volume 44 / Issue 8 / June 2014
- Published online by Cambridge University Press:
- 13 September 2013, pp. 1653-1662
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Background
Previous studies of bipolar disorders indicate that childhood abuse and substance abuse are associated with the disorder. Whether both influence the clinical picture, or if one is mediating the association of the other, has not previously been investigated.
MethodA total of 587 patients with bipolar disorders were recruited from Norway and France. A history of childhood abuse was obtained using the Childhood Trauma Questionnaire. Diagnosis and clinical variables, including substance abuse, were based on structured clinical interviews (Structured Clinical Interview for DSM-IV Axis I disorders or French version of the Diagnostic Interview for Genetic Studies).
ResultsCannabis abuse was significantly associated with childhood abuse, specifically emotional and sexual abuse (χ2 = 8.63, p = 0.003 and χ2 = 7.55, p = 0.006, respectively). Cannabis abuse was significantly associated with earlier onset of the illness (z = −4.17, p < 0.001), lifetime history of at least one suicide attempt (χ2 = 11.16, p = 0.001) and a trend for rapid cycling (χ2 = 3.45, p = 0.06). Alcohol dependence was associated with suicide attempt (χ2 = 10.28, p = 0.001), but not with age at onset or rapid cycling. After correcting for possible confounders and multiple testing, a trend was observed for an interaction between cannabis abuse and childhood abuse and suicide attempt (logistic regression: r2 = 0.06, p = 0.039). Significant additive effects were also observed between cannabis abuse and childhood abuse on earlier age at onset (p < 0.001), increased rapid cycling and suicide attempt (logistic regression: r2 = 0.03–0.04, p < 0.001). No mediation effects were observed; childhood abuse and cannabis abuse were independently associated with the disorder.
ConclusionsOur study is the first to demonstrate significant additive effects, but no mediation effects, between childhood abuse and cannabis abuse on increased clinical expressions of bipolar disorders.
Summary for Policy Makers
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- By Thomas B. Johansson, Lund University, Nebojsa Nakicenovic, International Institute for Applied Systems Analysis and Vienna University of Technology, Anand Patwardhan, Indian Institute of Technology-Bombay), Luis Gomez-Echeverri, International Institute for Applied Systems Analysis, Rangan Banerjee, Indian Institute of Technology, Sally M. Benson, Stanford University, Daniel H. Bouille, Bariloche Foundation, Abeeku Brew-Hammond, Kwame Nkrumah University of Science and Technology, Aleh Cherp, Central European University, Suani T. Coelho, National Reference Center on Biomass, University of São Paulo, Lisa Emberson, Stockholm Environment Institute, University of York, Maria Josefina Figueroa, Technical University, Arnulf Grubler, International Institute for Applied Systems Analysis, Austria and Yale University, Kebin He, Tsinghua University, Mark Jaccard, Simon Fraser University, Suzana Kahn Ribeiro, Federal University of Rio de Janeiro, Stephen Karekezi, AFREPREN/FWD, Eric D. Larson, Princeton University and Climate Central, Zheng Li, Tsinghua University, Susan McDade, United Nations Development Programme), Lynn K. Mytelka, United Nations University-MERIT, Shonali Pachauri, International Institute for Applied Systems Analysis, Keywan Riahi, International Institute for Applied Systems Analysis, Johan Rockström, Stockholm Environment Institute, Stockholm University, Hans-Holger Rogner, International Atomic Energy Agency, Joyashree Roy, Jadavpur University, Robert N. Schock, World Energy Council, UK and Center for Global Security Research, Ralph Sims, Massey University, Kirk R. Smith, University of California, Wim C. Turkenburg, Utrecht University, Diana Ürge-Vorsatz, Central European University, Frank von Hippel, Princeton University, Kurt Yeager, Electric Power Research Institute and Galvin Electricity Initiative
- Global Energy Assessment Writing Team
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- Book:
- Global Energy Assessment
- Published online:
- 05 September 2012
- Print publication:
- 27 August 2012, pp 3-30
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Summary
Introduction
Energy is essential for human development and energy systems are a crucial entry point for addressing the most pressing global challenges of the 21st century, including sustainable economic and social development, poverty eradication, adequate food production and food security, health for all, climate protection, conservation of ecosystems, peace and security. Yet, more than a decade into the 21st century, current energy systems do not meet these challenges.
A major transformation is therefore required to address these challenges and to avoid potentially catastrophic future consequences for human and planetary systems. The Global Energy Assessment (GEA) demonstrates that energy system change is the key for addressing and resolving these challenges. The GEA identifies strategies that could help resolve the multiple challenges simultaneously and bring multiple benefits. Their successful implementation requires determined, sustained and immediate action.
Transformative change in the energy system may not be internally generated; due to institutional inertia, incumbency and lack of capacity and agility of existing organizations to respond effectively to changing conditions. In such situations clear and consistent external policy signals may be required to initiate and sustain the transformative change needed to meet the sustainability challenges of the 21st century.
The industrial revolution catapulted humanity onto an explosive development path, whereby, reliance on muscle power and traditional biomass was replaced mostly by fossil fuels. In 2005, some 78% of global energy was based on fossil energy sources that provided abundant and ever cheaper energy services to more than half the people in the world.
Technical Summary
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- By Thomas B. Johansson, Lund University, Nebojsa Nakicenovic, International Institute for Applied Systems Analysis and Vienna University of Technology, Anand Patwardhan, Indian Institute of Technology, Luis Gomez-Echeverri, International Institute for Applied Systems Analysis, Doug J. Arent, National Renewable Energy Laboratory, Rangan Banerjee, Indian Institute of Technology, Sally M. Benson, Stanford University, Daniel H. Bouille, Bariloche Foundation, Abeeku Brew-Hammond, Kwame Nkrumah University of Science and Technology, Aleh Cherp, Central European University, Suani T. Coelho, National Reference Center on Biomass, University of São Paulo, Lisa Emberson, Stockholm Environment Institute, University of York, Maria Josefina Figueroa, Technical University, Arnulf Grubler, International Institute for Applied Systems Analysis, Austria and Yale University, Kebin He, Tsinghua University, Mark Jaccard, Simon Fraser University, Suzana Kahn Ribeiro, Federal University of Rio de Janeiro, Stephen Karekezi, AFREPREN/FWD, Eric D. Larson, Princeton University and Climate Central, Zheng Li, Tsinghua University, Susan McDade, United Nations Development Programme, Lynn K. Mytelka, United Nations University-MERIT, Shonali Pachauri, International Institute for Applied Systems Analysis, Keywan Riahi, International Institute for Applied Systems Analysis, Johan Rockström, Stockholm Environment Institute, Stockholm University, Hans-Holger Rogner, International Atomic Energy Agency, Joyashree Roy, Jadavpur University, Robert N. Schock, World Energy Council, UK and Center for Global Security Research, Ralph Sims, Massey University, Kirk R. Smith, University of California, Wim C. Turkenburg, Utrecht University, Diana Ürge-Vorsatz, Central European University, Frank von Hippel, Princeton University, Kurt Yeager, Electric Power Research Institute and Galvin Electricity Initiative
- Global Energy Assessment Writing Team
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- Book:
- Global Energy Assessment
- Published online:
- 05 September 2012
- Print publication:
- 27 August 2012, pp 31-94
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Summary
Introduction
Energy is essential for human development and energy systems are a crucial entry point for addressing the most pressing global challenges of the 21st century, including sustainable economic, and social development, poverty eradication, adequate food production and food security, health for all, climate protection, conservation of ecosystems, peace, and security. Yet, more than a decade into the 21st century, current energy systems do not meet these challenges.
In this context, two considerations are important. The first is the capacity and agility of the players within the energy system to seize opportunities in response to these challenges. The second is the response capacity of the energy system itself, as the investments are long-term and tend to follow standard financial patterns, mainly avoiding risks and price instabilities. This traditional approach does not embrace the transformation needed to respond properly to the economic, environmental, and social sustainability challenges of the 21st century.
A major transformation is required to address these challenges and to avoid potentially catastrophic consequences for human and planetary systems. The GEA identifies strategies that could help resolve the multiple challenges simultaneously and bring multiple benefits. Their successful implementation requires determined, sustained, and immediate action.
The industrial revolution catapulted humanity onto an explosive development path, whereby reliance on muscle power and traditional biomass was replaced mostly by fossil fuels. In 2005, approximately 78% of global energy was based on fossil energy sources that provided abundant and ever cheaper energy services to more than half the world's population.
Unmet needs in patients with first-episode schizophrenia: a longitudinal perspective
- K. Landolt, W. Rössler, T. Burns, V. Ajdacic-Gross, S. Galderisi, J. Libiger, D. Naber, E. M. Derks, R. S. Kahn, W. W. Fleischhacker
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- Journal:
- Psychological Medicine / Volume 42 / Issue 7 / July 2012
- Published online by Cambridge University Press:
- 21 November 2011, pp. 1461-1473
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Background
This study aimed to identify the course of unmet needs by patients with a first episode of schizophrenia and to determine associated variables.
MethodWe investigated baseline assessments in the European First Episode Schizophrenia Trial (EUFEST) and also follow-up interviews at 6 and 12 months. Latent class growth analysis was used to identify patient groups based on individual differences in the development of unmet needs. Multinomial logistic regression determined the predictors of group membership.
ResultsFour classes were identified. Three differed in their baseline levels of unmet needs whereas the fourth had a marked decrease in such needs. Main predictors of class membership were prognosis and depression at baseline, and the quality of life and psychosocial intervention at follow-up. Depression at follow-up did not vary among classes.
ConclusionsWe identified subtypes of patients with different courses of unmet needs. Prognosis of clinical improvement was a better predictor for the decline in unmet needs than was psychopathology. Needs concerning social relationships were particularly persistent in patients who remained high in their unmet needs and who lacked additional psychosocial treatment.
Contributors
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- By Eric Adler, Anoushka Afonso, Dean B. Andropoulos, Adel Bassily-Marcus, Yaakov Beilin, Elliott Bennett-Guerrero, Howard H. Bernstein, Marc J. Bloom, David Bronheim, Albert T. Cheung, Samuel DeMaria, Deborah Dubensky, James B. Eisenkraft, Jonathan Elmer, Liza J. Enriquez, Jonathan Epstein, Jeffrey M. Feldman, Gregory W. Fischer, Brigid Flynn, Jennifer A. Frontera, Richard S. Gist, Glenn P. Gravlee, Christina L. Jeng, Ronald A. Kahn, Jenny Kam, Mukul Kapoor, Jung Kim, Roopa Kohli-Seth, Aaron F. Kopman, Tuula S. O. Kurki, Andrew B. Leibowitz, Matthew Levin, Adam I. Levine, Michael S. Lewis, Justin Lipper, Martin London, Michael L. McGarvey, Alexander J. C. Mittnacht, Timothy Mooney, Diana Mungall, Yasuharu Okuda, Peter J. Papadakos, Jayashree Raikhelkar, Lakshmi V. Ramanathan, David L. Reich, Meg A. Rosenblatt, Corey Scurlock, Tamas Seres, Linda Shore-Lesserson, Marc E. Stone, Daniel M. Thys, Judit Tolnai, David Wax, Nathaen Weitzel
- David L. Reich, Mount Sinai School of Medicine, New York
- Edited by Ronald A. Kahn, Mount Sinai School of Medicine, New York, Alexander J. C. Mittnacht, Mount Sinai School of Medicine, New York, Andrew B. Leibowitz, Mount Sinai School of Medicine, New York, Marc E. Stone, Mount Sinai School of Medicine, New York, James B. Eisenkraft, Mount Sinai School of Medicine, New York
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- Book:
- Monitoring in Anesthesia and Perioperative Care
- Published online:
- 05 July 2011
- Print publication:
- 08 August 2011, pp vii-ix
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Contributors
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- By Ashok Agarwal, Carrie Bedient, Nick Brook, Michelle Catenacci, Ying Cheong, Francisco Domínguez, Thomas Elliott, Sandro C. Esteves, Tommaso Falcone, Gabriel de la Fuente, Eugene Galdones, Juan A. Garcia-Velasco, David K. Gardner, Tamara Garrido, Robert B. Gilchrist, Georg Griesinger, Roy Homburg, Jeanine Cieslak Janzen, Mark T. Johnson, Jennifer Kahn, David L. Keefe, Efstratios M Kolibianakis, Laurie J. McKenzie, Nick Macklon, David Meldrum, Ashley R. Mott, Tetsunori Mukaida, Zsolt Peter Nagy, Edurne Novella-Maestre, Chris O’Neill, Chikaharo Oka, Steven F. Palta, Lewis K. Pannell, Antonio Pellicer, Valeria Pugni, Botros R. M. B. Rizk, Christopher B. Rizk, Claude Robert, Denny Sakkas, Hassan N. Sallam, William B. Schoolcraft, Lonnie D. Shea, Carlos Simón, Manuela Simoni, Marc-Andre Sirard, Johan E. J. Smitz, Eric S. Surrey, Jan Tesarik, Raquel Mendoza Tesarik, Jeremy G. Thompson, Andrew J. Watson, Teresa K. Woodruff
- Edited by David K. Gardner, University of Melbourne, Botros R. M. B. Rizk, University of South Alabama, Tommaso Falcone
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- Book:
- Human Assisted Reproductive Technology
- Published online:
- 16 May 2011
- Print publication:
- 31 March 2011, pp ix-xii
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